Estimation of the odour intensity of air samples undergoing biofiltration process using electronic nose and artificial neural network

Biofiltration is one of the techniques used to reduce odorants in the air. It is based on the aerobic degradation of pollutants by microorganisms located in the filter bed. The research presents the possibility of using the electronic nose prototype combined with artificial neural network for estimation of the odour intensity of toluene contaminated air samples. The study was conducted using 3-section biotrickling filter settled with selected environmental isolates of Candida fungi during 21 days. As a result of the studies, it was found that the electronic nose prototype along with the proposed artificial neural network can be successfully used to estimate of the odour intensity of toluene contaminated air samples undergoing biofiltration process.